Machine Learning Engineer

Job Description :

Build, train and deploy AI/ML models and applications for banking using Python, NLP, LLMs and cloud technologies to solve complex business problems and generate actionable insights.

Requirements :

- 10+ years in Data Science/ML Engineering with expertise in Python, NLP, LLMs, LangChain, FastAPI, Azure, TensorFlow/PyTorch, MLOps and production ML deployment.

- BFSI experience preferred.

Key Responsibilities :

- Architect and deploy end-to-end machine learning pipelines that automate complex financial processes and improve predictive accuracy for banking operations.

- Develop advanced predictive models to identify market trends, customer behavior patterns, and risk exposure, enabling stakeholders to make data-driven strategic decisions.

- Implement sophisticated NLP techniques to extract insights from unstructured financial documents, regulatory reports, and customer interaction logs.

- Lead the optimization of statistical models to ensure high performance, scalability, and compliance with stringent financial industry standards.

- Mentor junior data scientists and engineers by fostering a culture of technical excellence and rigorous analytical methodology within the team.

- Collaborate with IT and data engineering teams to ensure seamless integration of ML models into existing banking infrastructure and production environments.

Skills

Python, Machine Learning, NLP, LLM, LangChain, FastAPI, Azure, Tensorflow, PyTorch, Artificial Intelligence, MLOps